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Interchange two vectors.
import gswap from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-gswap@deno/mod.js';You can also import the following named exports from the package:
import { ndarray } from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-gswap@deno/mod.js';Interchanges vectors x and y.
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];
gswap( x.length, x, 1, y, 1 );
// x => [ 6.0, 7.0, 8.0, 9.0, 10.0 ]
// y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ]The function has the following parameters:
- N: number of indexed elements.
- x: first input array.
- strideX: index increment for
x. - y: second input array.
- strideY: index increment for
y.
The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to swap in reverse order every other value in x with the first N elements of y,
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];
gswap( 3, x, -2, y, 1 );
// x => [ 9.0, 2.0, 8.0, 4.0, 7.0, 6.0 ]
// y => [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]Note that indexing is relative to the first index. To introduce an offset, use typed array views.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
// Initial arrays...
var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
// Swap in reverse order every other value from `x1` with `y1`...
gswap( 3, x1, -2, y1, 1 );
// x0 => <Float64Array>[ 1.0, 12.0, 3.0, 11.0, 5.0, 10.0 ]
// y0 => <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]Interchanges vectors x and y using alternative indexing semantics.
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];
gswap.ndarray( x.length, x, 1, 0, y, 1, 0 );
// x => [ 6.0, 7.0, 8.0, 9.0, 10.0 ]
// y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ]The function has the following additional parameters:
- offsetX: starting index for
x. - offsetY: starting index for
y.
While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to swap every other value in x starting from the second value with the last N elements in y where x[i] = y[n], x[i+2] = y[n-1],...,
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 );
// x => <Float64Array>[ 1.0, 12.0, 3.0, 11.0, 5.0, 10.0 ]
// y => <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]- If
N <= 0, both functions leavexandyunchanged. - Both functions support array-like objects having getter and setter accessors for array element access (e.g.,
@stdlib/array-complex64). gswap()corresponds to the BLAS level 1 functiondswapwith the exception that this implementation works with any array type, not just Float64Arrays. Depending on the environment, the typed versions (dswap,sswap, etc.) are likely to be significantly more performant.
import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@deno/mod.js';
import gswap from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-gswap@deno/mod.js';
var opts = {
'dtype': 'float64'
};
var x = discreteUniform( 10, 0, 500, opts );
console.log( x );
var y = discreteUniform( x.length, 0, 255, opts );
console.log( y );
// Swap elements in `x` and `y` starting from the end of `y`:
gswap( x.length, x, 1, y, -1 );
console.log( x );
console.log( y );@stdlib/blas-base/dswap: interchange two double-precision floating-point vectors.@stdlib/blas-base/gcopy: copy values from x into y.@stdlib/blas-base/sswap: interchange two single-precision floating-point vectors.@stdlib/blas-gswap: interchange two vectors.
This package is part of stdlib, a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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